the identification of binding mode for arabidopsis thaliana 7-keto-8

The Identification of Binding Mode for Arabidopsis thaliana Bull. Korean Chem. Soc. 2012, Vol. 33, No. 5 1597

http://dx.doi.org/10.5012/bkcs.2012.33.5.1597

The Identification of Binding Mode for Arabidopsis thaliana

7-Keto-8-aminopelargonic Acid Synthase (AtKAPAS) Inhibitors

Jae Eun Cho, Sun Young Kang, Jung Sup Choi,† Young Kwan Ko,† In Taek Hwang,† and Nam Sook Kang*

Graduate School of New Drug Discovery and Development, Chungnam National University, Deajeon 305-764, Korea*E-mail: [email protected]

†Korea Research Institute of Chemical Technology, P.O. Box 107, Yuseong-gu, Daejeon 305-600, Korea

Received January 18, 2012, Accepted February 9, 2012

In this study, we determined the 3D-structure of Arabidopsis thaliana KAPAS by homology modeling. We

then investigated the binding mode of compounds obtained from in-house library using computational docking

methods. From the flexible docking study, we achieved high dock scores for the active compounds denoted in

this study as compound 3 and compound 4. Thus, we highlight the flexibility of specific residues, Lys 312 and

Phe 172, when used in active sites.

Key Words : KAPAS, Herbicides, Homology modeling, Docking

Introduction

Research on the topic of herbicides has advanced during

the past 50 years to the point that it can now protect crops

and elevate the quality and quantity of agricultural products.

However, the successful development of herbicides has

decreased recently owing to new environmental regulations.

To overcome this problem, there is an urgent need for new

herbicidal targets and new techniques.1

While the traditional approach to discover lead compounds

heavily depends on serendipity given the poor understanding

of biological modes of actions, the structure-based approach

utilizes the structure of appropriate target proteins which

have well-known binding sites for possible rational designs.

The structure-based approach uses only appropriate target

proteins instead of the entire plant for in vivo testing.2 In

order to perform a structure-based assay, it is necessary to

determine a potent target with a thorough understanding of

the mechanism of action of the target.

Several enzymes in plants are known to be essential

enzymes, meaning that they are crucial for the plant’s sur-

vival. Disrupting a single essential enzyme leads to severe

disorder in the metabolism of the plant, ultimately causing a

lethal phenotype to arise. 7-keto-8-aminopelargonic acid

synthase from Arabidopsis thaliana plants (AtKAPAS),

introduced in this research, is a new potent herbicide target

which is involved in the early steps of the creation of the

biotin biosynthesis pathway. AtKAPAS as pyridoxal 5'-phos-

phate-dependent enzyme catalyzes the decarboxylative con-

densation of L-alanine with pimeloyl-CoA in a stereo

specific manner to form KAPA, coenzyme A, and carbon

dioxide in the first committed step ofbiotin biosynthesis.

Inhibiting AtKAPAS leads to significant changes in the

phenotype, such as growth inhibition, severe growth retarda-

tion, and the creation of lethal phenotypes.3

Although the physiological systems of human and plants

are different in various ways, the misuse of agricultural

chemicals can be extremely harmful to humans. Therefore,

herbicides must follow strict toxicity regulations that are in

place to prevent harm to humans. As mentioned above, the

novel herbicidal target 7-keto-8-aminopelargonic acid syn-

thase functions in the initial steps of the biosynthetic path-

ways of biotin (vitamin H) in plants and microorganisms.

Because biosynthetic steps of biotin exist only in plants, we

expect that the inhibition of the potent target AtKAPAS will

not affect the human metabolic system.1,3 A few publications

have also reported beneficial effects of AtKAPAS as a

potential herbicidal target.Hwang et al. described the possi-

bility of AtKAPAS as a potential herbicide target enzyme

and chemical validation of triphenyltin acetate as a lead

compound for the AtKAPAS inhibition in vitro and in vivo.1

They also suggested AtKAPAS can be a useful target for the

rational design of inhibitors in the hope of developing new

herbicides. Therefore, we aim to obtain potential AtKAPAS

inhibitors using the knowledge-based computational infor-

matics method in this research. We described the 3D-struc-

ture of AtKAPAS via theoretical method and the binding

mode for AtKAPAS and its inhibitors obtained from in vitro

assay for in house compounds.

Experimental Section

Building a Homology Model of AtKAPAS. To apply the

structure-based drug design (SBDD) method using current

knowledge of protein and drug interactions, a three-

dimensional protein structure is necessary.4 Because the

known protein crystal structural information of 7-keto-8-

aminopelargonic acid synthase from an experiment was

absent, a homology model of AtKAPAS was constructed

from its amino acid sequence (Table 1). To obtain the 3D-

structure of AtKAPAS, a hierarchical protein structure

modeling approach was adopted based on secondary-struc-

ture enhanced Profile-Profile threading Alignment (PPA)

and iterative implementation by the Threading ASSEmbly

1598 Bull. Korean Chem. Soc. 2012, Vol. 33, No. 5 Jae Eun Cho et al.

Refinement (TASSER) program.5 We obtained five candi-

date models for the three-dimensional structure of AtKAPAS

and then performed molecular dynamics simulations with

the use of the CHARMM force field (version 27.0)6 with

default parameters interfaced with Accelrys Discovery

Studio 3.1. To identify binding sites, we collected the crystal

structures of homologous proteins with AtKAPAS as

templates from the RCSB Protein Data Bank (PDB) based

on three different categories: structural similarity, binding

site similarity, functional similarity. Ten different protein

crystal structures originating from different species but

structurally similar to AtKAPAS were selected. The binding

site sequence and conformation of the target protein are

particularly important here compared to other sites. There-

fore, we found 10 different PDB hits which are similar in

terms of their binding site to AtKAPAS. A comparison

between each PDB hit and the AtKAPAS biding site

sequence was done. The results are denoted using root mean

square deviation (RMSD) values ranging from 1.83 to 3.51,

as shown in Table 2. To identify the binding mode of

AtKAPAS, 10 different enzymes (PDB code; 1FC4,7 1DJE,8

2WKA,9 2BWO,10 3KKI,11 3DXV,12 3DXW,12 2OAT,13

1GBN,14 and 1MLY15) with different functions originating

from different species were superimposed (Figure 1). Con-

sequently, we found that several residues were crucial for

protein-ligand interactions. His 210 mainly forms a π-π

interaction or a π-cation interaction with the ligands, and all

of the reference proteins contain histidine residue at a

position homologous to the AtKAPAS. Adjacent to His 210,

Phe 172 forms a π-π interaction with compounds that have

an aromatic ring moiety as well. 50% of proteins have

phenyl residue at a similar position; however, its con-

formation was considerably different. As shown in Figure 1,

conformation of Phe 172 residue of our homology model,

shown in yellow, is uniquely folded toward the active site

cavity as opposed to the phenyl residues of the reference

PDB. To confirm the effect of Phe 172, we undertook a

flexible docking. Lys 312 also plays an important role as a

hydrogen bond donor in the active site. All reference

Table 1. Single letter amino acid sequence for AtKAPAS

10 20 30 40 50 60

madhswdktv eeavnvlesr qilrslrpic msrqneeeiv ksranggdgy evfdglcqwd

70 80 90 100 110 120

rtsvevsvsi ptfqkwlhde psngeeifsg dalaecrkgr fkklllfsgn dylglsshpt

130 140 150 160 170 180

isnaaanavk eygmgpkgsa licgyttyhr llesslaqlk kkedclvcpt gfaanmaamv

190 200 210 220 230 240

aigsvaslla asgkplknek vaifsdalnh asiidgvrla erqgnvevfv yrhcdmyhln

250 260 270 280 290 300

sllsnckmkr kvvvtdslfs mdgdfapmee lsqlrkkygf llviddahgt fvcgengggv

310 320 330 340 350 360

aeefnceadv dlcvgtlska agchggfiac skkwkqliqs rgrsfifsta ipvpmaaaay

370 380 390 400 410 420

aavvvarkei wrrkaiwerv kefkelsgvd isspiislvv gnqekalkas ryllksgfhv

430 440 450 460 470 480

mairpptvpp nscrlrvtls aahttedvkk litalsscld fdntathips flfpkl

Table 2. Sequence similarity and RMSD between 10 referencePDB proteins

PDB code Sequence RMSD

1FC4 36.3 1.83

1DJE 39.5 1.66

2BWO 39.6 1.59

2WKA 32.2 2.42

3KKI 30.3 2.64

3DXV 16.6 3.26

3DXW 16.8 3.25

2OAT 15.7 3.38

1GBN 15.6 3.43

1MLY 15.5 3.51

Figure 1. The superimposed 10 known enzymes (PDB code:1FC4, 1DJE, 2WKA, 2BWO, 3KKI, 3DXV, 3DXW, 2OAT,1GBN, and 1MLY). The yellow colored structure represents ourhomology model and the overlaped predominantly importantresides in active site are elaborated on the right side of the entireprotein alignment.


enzymes showed the lysine residue at an analogous location

which led to π-cation interaction and hydrogen bonding

interaction with its ligand. In addition, due to its com-

paratively free long aliphatic chain,lysine residue was very

flexible. Lysine residues superimposed onto the analogous

site verified its flexibility. By superimposing the binding

sites of other similar proteins,we reached the conclusion that

the residues His 210, Phe 172 and Lys 312 play major roles

at the binding site. This research will therefore highlight the

ligand binding site residues and its flexibility to search for

potent hits.

Rigid Docking. As a structure-based drug design, we used

an automated docking method.16 To dock the compounds as

shown in Table 3 into the protein active site, we used the

rigid docking method implemented in Discovery Studio 3.1

(Accelrys, Inc.), which adopts a Monte-Carlo algorithm to

generate ligand conformations and docks the generated

ligands into the active site using a shape-based filtering

method. The rigid docking process consists of two main

steps: defining a binding cavity and docking ligands onto the

defined cavity.17 The AtKAPAS protein as obtained from the

homology model needs to be prepared before the docking

process is initiated. To prepare the protein, the CHARMM

force field was assigned and the docking cavity was defined

using the advanced define and edit binding site tool module.

Ligands also should be prepared with low-energy confor-

mations so as to be docked onto a ‘clean’ protein. The

protocol ‘Generate Conformations’ in Discovery Studio 3.1

was used to obtain three-dimensional conformations of each

ligand. In-house 17 ligands were generated by the protocol

‘Generate Conformation’ with the conformation method

‘BEST’, and the CHARMM force field was applied. For an

interaction filter, Lys 312 was selected.

Flexible Docking. Various docking methods are utilized

by researchers. Each approach was developed by focusing

on different aspects of docking. One of the factors deter-

mining the accuracy of docking is protein flexibility. Much

emphasis has been placed on the conformational changes of

protein binding sites, where different ligands form inter-

actions. The Flexible Docking protocol of Discovery Studio

3.1 allows receptor flexibility during the docking of ligands.18-20

To confirm the flexibility of the selected residues in the

AtKAPAS active site, three different sets of residues were

defined as flexible docking 1; Lys 312, flexible docking 2;

Phe 172, and flexible docking 3; Lys 312 and Phe 172. For

the flexible docking 1 set, only the residue Lys 312 was

assigned to move when flexible docking was underway.

17 pre-processed ligands were docked into the prepared

AtKAPAS homology model. The ‘BEST’ conformation

method was selected to generate three-dimensional ligands

with stable energy levels, and other parameters were left

with the default values. The residue Phe 172 was selected for

the second flexible docking trial with the same parameters

used with the flexible docking 1 set. To validate the effect of

both residues, Lys 312 and Phe 172 were set as the flexible

docking 3 group, and these residues were moved while

flexible docking was underway.

Table 3. The structures of the used 17 compounds and its biologicalactivies

Compounds Structure pIC50

1 5.48

2 5.36

3 6.23

4 6.20

5 4.25

6 4.27

7 4.39

8 4.33

9 4.95

10 4.95

11 4.38

12 5.68

13 5.02

14 5.36

15 5.97

16 5.90

17 5.36


In vitro Assay. Pimeloyl CoA was synthesized according

to the method described previously.21 AtKAPAS activity was

determined according to the method described previously22

usinga linked assay by monitoring the increase in absorption

of NADH at 340 nm using a Microplate Spectrophotometer

(Benchmark Plus, Bio-rad, USA), thermostatically controll-

ed at 30 oC. A typical assay contained 20 mM potassium

phosphate (pH 7.5), 1 mM α-ketoglutarate, 0.25 mM

thiamine pyrophosphate, 1 mM NAD+, 3 mM MgCl2, 0.1

unit of α-ketoglutaratedehydrogenase, and 2 to 10 μg of

AtKAPAS in a total volume of 200 μL. L-Alanine and

pimeloyl-Co A were added to give the desirable final con-

centrations. Prior to analysis, enzyme samples were dialyzed

for 2 hours at 4 oC against 20 mM potassium phosphate (pH

7.5) containing 100 μM PLP. The KAPAS concentration in

allanalyses was 10 μM in 20 mM potassium phosphate (pH

7.5) and the concentrations of each compound were 0.1 to

250 μM. Reference corvettes contained all other compounds

except inhibitor.

Results and Discussion

Significant results were obtained from the docking pro-

cesses undertaken in this study. The rigid docking output

scores of the in-house compounds are shown in Table 4. The

most active compounds, in this case compound 3 and

compound 4, obtained high dock scores of 104.21 and

105.47, respectively. Moreover, active ligands which have

IC50 (μM) values 1.07 and 1.26 (compound 15 and compound

16, respectively) formed a stable docking pose (Figure 2)

with high dock scores 106.03 and 72.5, respectively.

However, other active compounds, specifically compound 1,

compound 9 and compound 10, showed rather low dock

scores, as shown in Table 3.

To obtain a better docking result, we used a flexible

docking strategy, as mentioned in the experimental section.

In the result for flexible docking 1, which stipulated that the

Lys 312 residue of the AtKAPAS model is set to move, most

of the compounds formed a stable conformation and formed

interactions with the AtKAPAS homology model (Table 5).

Table 4. The result of rigid docking

Compound Dock score pIC50a

1 40.40 5.48

2 67.64 5.36

3 104.21 6.23

4 105.47 6.20

5 55.73 4.25

6 42.30 4.27

7 50.67 4.39

8 51.67 4.33

9 58.72 4.95

10 45.79 4.95

11 49.91 4.38

12 63.13 5.68

13 52.84 5.02

14 52.99 5.36

15 106.03 5.97

16 72.51 5.90

17 52.31 5.36

apIC50 = −logIC50

Figure 2. The docking pose from the process of rigid docking andflexibie docking (a~d). The blue dashed line represents hydrogenbonding interaction and the orange dashed line represents the π-cation and π-π interaction. The docked ligand, compound 3, iscolored with green and the crystal ligand of 1FC4 colored withyellow is overlapped as a reference compound. The docking posefromthe process of rigid docking is shown in (a). From the processof flexible dockset 1, the docking pose of compound 3 wasobtained as shown in (b). The docking pose shown in (c) achievedfrom the process of flexible docking set 2. In addition, the dockingpose of compound 3 shown in (d) obtained from the process offlexible docking set 3.

Table 5. The result of flexible docking set 1

Compound Dock score pIC50

1 74.00 5.48

2 83.14 5.36

3 134.03 6.23

4 125.27 6.20

5 53.40 4.25

6 50.83 4.27

7 59.46 4.39

8 54.40 4.33

9 105.54 4.95

10 76.74 4.95

11 74.36 4.38

12 83.56 5.68

13 76.92 5.02

14 80.04 5.36

15 131.67 5.97

16 96.88 5.90

17 75.41 5.36


According to the docking result, the diverse conformation of

Lys 312 directly affects the pose of the ligands and the

related activity. The Lys 312 residue forms a hydrogen bond

or undergoes the π-cation interaction mostly with the oxygen

moiety of the ligand by flexibly moving through the protein

cavity (Figure 2). Interestingly, we obtained relatively high

dock scores for compound 1, compound 9 and compound

10. This was unobtainable with the rigid docking process.

The correlation coefficient between pIC50 and the dock score

for the flexible docking 1 set was 0.72, as shown in Figure 3.

By flexibly moving the residue Phe 172 while the flexible

docking 2 process was underway, a better result than the

flexible docking 1 process was obtained (Table 6). The

flexibility of the Phe 172 residue has a significant effect on

the ligand binding at the AtKAPAS active site. The phenyl

ring is particularly important to form the π-π interaction with

compounds. According to the docking result, high dock

scores of 119.91 and 113.06 were the result with the most

active compounds, compound 3 and compound 4. In

addition, active compounds with IC50 values lower than 1.3

μM received dock scores higher than 90 with a stable

conformation. Conversely, the inactive compounds of

compound 5 through compound 8 as well as compound 11

obtained relatively low dock scores (Table 6).

The two specific AtKAPAS residues, Lys 132 and Phe

172, can be moved mutually for the flexible docking 3

process. The result shows the clear discrepancy between an

active compound and an inactive compound (Table 7). The

flexible docking 3 results showed a higher correlation

between pIC50 and the dock score compared to flexible

docking 2, whereas it had a slightly lower R2 value than the

flexible docking 2 result (Figure 5). Because the two

residues were set to move at the same time, more diverse

results could be obtained. As a result of several flexible

Figure 3. Correlation of IC50 and dock score for the flexibledocking set 1.



1 75.60 5.48

2 85.84 5.36

3 119.05 6.23

4 113.06 6.20

5 48.11 4.25

6 44.80 4.27

7 53.49 4.39

8 49.60 4.33

9 72.97 4.95

10 74.43 4.95

11 57.66 4.38

12 85.24 5.68

13 79.99 5.02

14 67.73 5.36

15 113.29 5.97

16 90.84 5.90

17 65.49 5.36



1 71.47 5.48

2 95.12 5.36

3 120.48 6.23

4 119.46 6.20

5 40.92 4.25

6 40.03 4.27

7 54.90 4.39

8 61.54 4.33

9 80.87 4.95

10 72.13 4.95

11 75.00 4.38

12 78.83 5.68

13 74.82 5.02

14 73.04 5.36

15 124.28 5.97

16 91.92 5.90

17 70.70 5.36

Figure 4. Correlation of IC50 and dock score for the flexibledocking set 2.


docking processes, this study emphasizes the flexibility of

several residues. Noticeably higher dock scores were obtain-

ed from flexible docking as compared to rigid docking. The

rigid Lys 312 residue mostly tends to form π-cation inter-

action with the aromatic moiety of compounds, allowing a

certain amount of space for compounds during the rigid

docking process. However, the flexible Lys 312 forms either

the π-cation interaction or the hydrogen bonding interaction

with hydrogen bond acceptors. The flexibility of the residue,

including Lys 312 and Phe 172, allows more space for

compounds, thus offering a better docking pose and dock

scores.

Conclusion

In this study, we determined the 3D-structure of AtKAPAS

by homology modeling. We then investigated the binding

mode of our in-house library using computational docking

methods. In the rigid docking of the in house compounds as

shown in Table 3, the most active compounds, in this case

compound 3 and compound 4, obtained high dock scores of

104.21 and 105.47, respectively. However, some active

compounds showed rather low dock scores. To obtain a

better docking result, we used a flexible docking strategy.

From the flexible docking study, we achieved high dock

scores and stable binding conformations for the active

compounds denoted in this study. Thus, we highlight the

flexibility of specific residues, Lys 312 and Phe 172, when

used in active sites. Furthermore, we are going to optimize

compound 3 and compound 4 using this homology model

for AtKAPAS.

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Figure 5. Correlation of IC50 and dock Score for the flexibledocking set 3.

the identification of binding mode for arabidopsis thaliana 7-keto-8

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